4 papers
Decoherence as Defence and the Magnitude of Noise Regularisation: A Rigorous N -Qubit Theory of Stochastic Quantum Neural Networks for Adversarially Robust Network Intrusion Detection
Gautier-Edouard Edouard Filardo
Stochastic quantum neural networks (SQNNs) encode neuronal activations as qubits, synaptic topology as entanglement, and neural noise through a Lindblad master equation. A recent c…
Crossed-Product von Neumann Algebras for Incompressible Navier--Stokes Flows and Spectral Complexity Indicators
Gautier-Edouard Edouard Filardo
We introduce a traceable operator-algebraic framework for incompressible transport on M= T3 (and, more generally, compact Riemannian manifolds endowed with a smooth invariant proba…
Enhancing NTRUEncrypt Security Using Markov Chain Monte Carlo Methods: Theory and Practice
Gautier-Edouard Filardo, Thibaut Heckmann
This paper presents a novel framework for enhancing the quantum resistance of NTRUEncrypt using Markov Chain Monte Carlo (MCMC) methods. We establish formal bounds on sampling effi…
A Stochastic Quantum Neural Network Model for Ai
Gautier-Edouard Filardo, Thibaut Heckmann
Artificial intelligence (AI) has drawn significant inspiration from neuroscience to develop artificial neural network (ANN) models. However, these models remain constrained by the…